{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,23]],"date-time":"2024-10-23T05:02:51Z","timestamp":1729659771534,"version":"3.28.0"},"reference-count":22,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T00:00:00Z","timestamp":1596240000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T00:00:00Z","timestamp":1596240000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T00:00:00Z","timestamp":1596240000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,8]]},"DOI":"10.1109\/case48305.2020.9216798","type":"proceedings-article","created":{"date-parts":[[2020,10,8]],"date-time":"2020-10-08T16:01:51Z","timestamp":1602172911000},"page":"1110-1115","source":"Crossref","is-referenced-by-count":18,"title":["Deep-Reinforcement-Learning-Based Semantic Navigation of Mobile Robots in Dynamic Environments"],"prefix":"10.1109","author":[{"given":"Linh","family":"Kastner","sequence":"first","affiliation":[]},{"given":"Cornelius","family":"Marx","sequence":"additional","affiliation":[]},{"given":"Jens","family":"Lambrecht","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"crossref","first-page":"529","DOI":"10.1038\/nature14236","article-title":"Human-level control through deep reinforcement learning","volume":"518","author":"mnih","year":"2015","journal-title":"Nature"},{"journal-title":"arXiv preprint arXiv 1604 07316","article-title":"End to end learning for self-driving cars","year":"2016","author":"bojarski","key":"ref11"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2019.8794062"},{"key":"ref13","first-page":"215","article-title":"Semantic scene analysis of scanned 3d indoor environments","author":"n\u00fcchter","year":"2003","journal-title":"VMV"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1155\/2018\/1627185"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/3317640.3317652"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2017.7989381"},{"first-page":"125","article-title":"Deep reinforcement learning hands-on: Apply modern rl methods, with deep q-networks, value iteration, policy gradients, trpo, alphago zero and more","year":"2018","author":"lapan","key":"ref17"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/BF00115009"},{"key":"ref19","doi-asserted-by":"crossref","DOI":"10.1609\/aaai.v30i1.10295","article-title":"Deep reinforcement learning with double q-learning","author":"van hasselt","year":"2016","journal-title":"THIRTIETH AAAI Conference on Artificial Intelligence"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.3390\/s19173699"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.robot.2016.11.012"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-17322-6_30"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.3390\/s19183837"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2014.6942731"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ROBOT.2004.1307456"},{"journal-title":"Introduction to Autonomous Mobile Robots","year":"2011","author":"siegwart","key":"ref2"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ETFA.2014.7005252"},{"key":"ref9","first-page":"1433","article-title":"Maximum entropy inverse reinforcement learning","volume":"8","author":"ziebart","year":"2008","journal-title":"AAAI"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2018.05.004"},{"journal-title":"arXiv preprint arXiv 2001 04786","article-title":"A markerless deep learning-based 6 degrees of freedom poseestimation for with mobile robots using rgb data","year":"2020","author":"k\u00e4stner","key":"ref22"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00038"}],"event":{"name":"2020 IEEE 16th International Conference on Automation Science and Engineering (CASE)","start":{"date-parts":[[2020,8,20]]},"location":"Hong Kong, Hong Kong","end":{"date-parts":[[2020,8,21]]}},"container-title":["2020 IEEE 16th International Conference on Automation Science and Engineering (CASE)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9210430\/9216730\/09216798.pdf?arnumber=9216798","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,22]],"date-time":"2022-11-22T12:59:03Z","timestamp":1669121943000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9216798\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8]]},"references-count":22,"URL":"https:\/\/doi.org\/10.1109\/case48305.2020.9216798","relation":{},"subject":[],"published":{"date-parts":[[2020,8]]}}}